25 March 2015| REF: J/N 123192
Department of Economic Development,
Jobs, Transport and Resources
VEET Energy Saver Incentive Scheme
Business Sector Energy Efficiency
Modelling
BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
Project details
Department of Economic Development, Jobs,
Transport and Resources
Energetics Contact
Kathryn Lucas-Healey
Gordon Weiss
Description
Prepared By
Reviewed By
Approved By
Approval Date
Version 1: Initial Draft
Gordon Weiss
Emma Fagan
Gordon Weiss
23/02/2015
Version 2: Revised version
Emma Fagan
Gordon Weiss
Gordon Weiss
25/03/2015
About Energetics
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Winner: BRW Client Choice Award for
Best Value
Finalists: BRW Client Choice Awards
for
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Service,
Most
Innovative, Outstanding Client Care
and Best Consulting Engineering Firm
(revenue <$50 Million)
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BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
Copyright
© 2015 Energetics. All rights reserved.
"Energetics" refers to Energetics Pty Ltd and any related entities.
This report is protected under the copyright laws of Australia and other countries as an unpublished work. This report contains
information that is proprietary and confidential to Energetics and subject to applicable Federal or State Freedom of Information
legislation, shall not be disclosed outside the recipient's company or duplicated, used or disclosed in whole or in part by the
recipient for any purpose other than for which the report was commissioned. Any other use or disclosure in whole or in part of
this information without the express written permission of Energetics is prohibited.
Disclaimer
The information contained in this document is of a general nature only and does not constitute personal financial product advice.
In preparing the advice no account was taken of the objectives, financial situation or needs of any particular person. Energetics
is authorised to provide financial product advice on derivatives to wholesale clients under the Corporations Act 2001 AFSL No:
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BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
Table of contents
TABLE OF CONTENTS
1.
Background ................................................................................................................................... 1
2.
Modelling the VEET scheme ........................................................................................................ 3
2.1.
Consideration of non-financial barriers ......................................................................................... 5
3.
Assumptions and parameters ....................................................................................................... 6
4.
Defining the measures .................................................................................................................. 9
4.1.
Large commercial and SME sectors ........................................................................................... 10
4.2.
Large industrial sector ................................................................................................................. 14
5.
Outcomes: Results of the modelling ........................................................................................... 17
5.1.
Business sector results ............................................................................................................... 17
5.2.
Results for certificate price scenarios ......................................................................................... 18
Appendix A.
Key assumptions ....................................................................................................... 25
Retail energy prices ........................................................................................................................... 25
Savings and cost of lighting upgrades ............................................................................................... 25
Payback thresholds ............................................................................................................................ 28
Appendix B.
Industrial and mining measures ................................................................................. 30
Appendix C.
Details of the measures ............................................................................................. 32
Contact details ..................................................................................................................................... 33
LIST OF FIGURES
Figure 1: Calculation of incentive level .................................................................................................... 3
Figure 2: Measure uptake for smaller measures – take up curves as a function of incentive percentage
................................................................................................................................................................. 4
Figure 3: Measure uptake for larger measures – take up curves as function of payback ...................... 4
Figure 4: Measures adopted.................................................................................................................... 4
Figure 5: Three year target with large business exclusion .................................................................... 17
Figure 6: Seven year target with large business exclusion ................................................................... 17
Figure 7: Seven year target without large business exclusion .............................................................. 18
Figure 8: Large commercial site energy consumption .......................................................................... 27
LIST OF TABLES
Table 1: Changes from previous VEET modelling .................................................................................. 2
Table 2: Key assumptions and parameters in the model ........................................................................ 6
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BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
Table 3: Parameters defining each measure .......................................................................................... 9
Table 4: Example of a measure .............................................................................................................. 9
Table 5: List of stationary energy savings measures by commercial market segment ......................... 12
Table 6: List of stationary energy savings measures by industrial market segment ............................. 14
Table 7: Extract from ClimateWorks database ...................................................................................... 16
Table 8: Three year scenario certificate prices ..................................................................................... 18
Table 9: Five year scenario certificate prices ........................................................................................ 19
Table 10: Certificates generated in the three year VEET scenario ....................................................... 19
Table 11: Certificates generated in five year VEET scenario ................................................................ 19
Table 12: Certificates generated by measure in 5.4 million certificates, five year VEET scenario ....... 20
Table 13: Model retail energy prices ..................................................................................................... 25
Table 14: Savings per lighting installation ............................................................................................. 26
Table 15: Energy consumption by building class .................................................................................. 27
Table 16: Derivation for commercial lighting upgrades in Victoria ........................................................ 28
Table 17: Industrial and mining measure parameters ........................................................................... 30
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1.
Background
On 1 January 2009 the Victorian Energy Saver Incentive (ESI) scheme was launched to promote the
uptake of energy efficiency improvements in residential premises. The scheme is established in the
Victorian Energy Efficiency Target Act 2007 (the Act). The objectives of the Act are to:
•
reduce greenhouse gas (GHG) emissions
•
encourage the efficient use of electricity and gas
•
encourage investment, employment and technology development in industries that supply
goods and services which reduce the use of electricity and gas by consumers.
The scheme is based on three year phases.
Phase 1 had an annual target of reducing lifetime GHG emissions by 2.7 million tonnes per annum in
the residential sector, which was doubled to 5.4 million per annum for Phase 2 for the period to 2015,
and expanded to include business and other non-residential sectors.
This objective of this review is to develop an appropriate target for Phase 3 of the VEET scheme.
In 2013 Energetics developed modelling as well as a number of scenarios examining business sector
energy efficiency activities (as provided in VEET Energy Model Input Final Assumptions Report 1 [the
2013 Assumption Report] and related spreadsheets). Sustainability Victoria modelled the residential
sector energy efficiency activities.
In this report, Energetics updates the modelling of business sector energy efficiency activities to
ensure that it is accurate and current. We also present a number of target scenarios to incorporate into
a model of the energy market, including energy efficiency measures pursued by the parts of the
Victorian business sector that buy energy from energy retailers rather than the wholesale market.
Constraints and limitations
There are a number of factors that may influence the growth of the VEET scheme in Victoria that have
not been included in this model. Non-market barriers such as split incentives and limited knowledge
and access to information about the benefits of energy efficiency activities, cannot be modelled
accurately.
There are also policies in Australia that may impact the pool of opportunities potentially taken up under
the VEET, particularly the Emissions Reduction Fund (ERF). While the influence of the ERF is
difficult to estimate before it begins, we see possible outcomes where engagement with the VEET
scheme is preferred. One such example arises where ERF assessment methodologies overlap with
the VEET. Project proponents may choose the VEET scheme as payment for emissions reductions is
made up front unlike the delivery model offered under the ERF. The lack of entry-level abatement
thresholds in the VEET may also make the scheme more attractive.
Ultimately market conditions and the price of both ACCUs and VEECs will determine how the pool of
opportunities offered under the VEET, may be impacted by the ERF.
1
“VEET Energy Model Input: Final assumptions report”, Energetics, 18 November 2013
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Changes from the 2013 model
The business sector energy efficiency modelling described in this report built on work done for the
2013 Assumption Report. A number of changes have been made to the earlier model and these are
outlined in Table 1 below.
Table 1: Changes from previous VEET modelling
Changes
Reference in this report
Measures for the large industrial sector are included
Section 4.2
A number of measures pertaining to the large
commercial and SME sectors have been removed or
combined
Section 4.1
Several measures pertaining to the large commercial
and SME sectors have been amended
Table 5
The electricity and natural gas prices are updated
Appendix A
The year by year decay of the savings due to a
measure has been changed
The value was changed from 0% to 3%.
Discount rate
The value for project based assessment (PBA)
measures was changed from 20% to 10%.
Detail in Section 2.
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2.
Modelling the VEET scheme
This report focuses on commercial energy efficiency measures and the assumptions used to model
their impact. The following section provides an overview of the functionality of the model.
Figure 1 to Figure 4 outline the process used to determine the number of certificates created for
different certificate prices. Each energy efficiency measure was defined according to adjustable
parameters such as the total pool of efficiency opportunities, the costs of implementation and the
average electricity and gas savings that will result. The model also includes adjustable parameters.
Examples include a certificate price ($/certificate2), a greenhouse gas (GHG) emissions factor and any
administrative fees associated with the creation of certificates.
The total number of certificates created depends on the annual GHG emissions savings, the duration
of the energy efficiency measure and the GHG emissions factor applied.
The incentive for participants is a function of the number of certificates created, multiplied by the value
of each certificate. The latter is net of any fees associated with the administration of the scheme.
The model calculates the uptake of measures based on the incentive to participate. One of two
approaches is used. For the less costly measures most suited to SME markets, the uptake is
calculated based on a simple relationship between the size of the incentive and the cost of the energy
efficiency measure. Figure 2 shows the uptake of simpler measures such as replacing an old
appliance. There is a default take-up curve plus one for low cost appliances and one for new
technologies (where there can be resistance to early adoption).
Incentive level
Annual energy
saving
Certificates
created
×
×(
Measure
life
×
VEET GHG
coefficients
Certificate
price
-
Administration
fees
=
Certificates
created
)=
Consumer
incentive
Figure 1: Calculation of incentive level
The 5% fee used within the model reflects the observed administrative cost reported in the
assessment of the ACT Government EEIS.
In determining the deemed savings for a project, the calculated emissions savings are discounted by
10% for each year of a project’s life up to 10 years. This differs from the 20% discount rate used in
prior VEET modelling. This discount provides a balance between what is an adequate incentive for
project proponents to drive energy saving measures and the need to ensure that certificates are only
created for genuine savings. The change in the discount rate is material and has resulted in an
effective project life of 5.5 years when generating VEECs as opposed to three years when using a
20% discount rate. It also results in a savings persistence of ten years rather than five.
The treatment of $0 certificate prices and the impact of the results are discussed in detail in section
2.1.
2
One certificate is intended to be equivalent to 1 tonne of lifetime greenhouse gas abatement.
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Measure uptake – Take up curves
BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
Consumer
incentive
÷
Cost of
measure
Incentive as % of
additional cost
=
Incentive as % of
additional cost
Uptake rate
function
=
Annual uptake
rate
Figure 2: Measure uptake for smaller measures – take up curves as a function of incentive percentage
If the commercial GHG emissions abatement measure is more costly and generally applicable to
larger businesses then it is more appropriate to use an approach based on the payback. Figure 3
shows the calculation. The payback threshold, which establishes when the energy efficiency measure
will be taken up, is a distribution function that reflects the range of thresholds for different participants.
Measure uptake – Payback
(
Cost of
measure
-
Payback
Consumer
incentive
)÷
Payback
threshold
Annual energy
saving
=
=
Payback
Annual uptake
rate
Measure uptake – Take up curves
Figure 3: Measure uptake for larger measures – take up curves as function of payback
Finally, the actual number of instances that the energy efficiency measure is adopted is expressed as
the uptake rate times the total pool of opportunity. Total uptake figures are managed by a constraint
that limits the maximum annual uptake to reflect the fact that the market has limited capacity to deliver
any one measure within a fixed period of time. See Figure 4 for an overview on how this functionality
works.
Annual uptake
rate
Maximum limit
on uptake
<×
Pool of
opportunity
=
Measures
adopted
Figure 4: Measures adopted
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2.1.
Consideration of non-financial barriers
Note that the assessments of payback periods within the model were undertaken on a purely financial
basis. There are a range of non-financial barriers that may also limit the interest in energy efficiency
projects. The impact of non-financial barriers is modelled through the use of payback periods that
have actually been seen in the market, rather than payback periods that would be implied by realistic
financial returns. As discussed in Section 3, the actual paybacks required by the market are as low as
1.75 years whereas projects with paybacks as high as 10 years would show a positive financial return.
The data that defines the take-up of a measure comes from a number of independent sources –
observed take-up of measures, reported costs to implement energy efficiency measures, savings
based on a basket of specific activities within a broad measure and forecasts of energy prices. For
instance, the measure “lighting upgrade” covers a broad range of potential activities that depend upon
the existing form of lighting and the replacement technology. It is possible that some measures will be
cost effective to some participants even if no incentive is in place. This is best considered as a
component of the business-as-usual case.
The business-as-usual take-up that is predicted by the model was deducted from the take-up at
various positive incentives (external to the VEET program) in order to give a true indication of the takeup driven by the incentive. As an example, if a measure saw 500 certificates generated at a $0
certificate price, and 10,000 generated a $15 certificate price, these 500 certificates are deducted from
the 10,000 certificates to give the actual impact of the incentive.
Note though that in the ‘real world’, factors such as an un-modelled increase in energy prices or a
significant drop in implementation cost will result in the measure becoming more cost effective and
therefore we would see take-up without any incentive. Similarly, a fall in energy prices or increase in
implementation costs will mean that measures are less attractive.
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3.
Assumptions and parameters
Table 2 outlines a number of key assumptions and parameters that define the overall properties of the
model. Some of these assumptions and parameters relate to the structure of the model and others
relate to the performance of the abatement measures.
Table 2: Key assumptions and parameters in the model
Item
Details
Business-asusual
Where activities involve the upgrade of equipment at the point of replacement (e.g. installing
a high efficiency motor at the time the motor needs replacing), the business–as-usual (BAU)
case assumes that a unit compliant with the Minimum Energy Performance Standards
(MEPS) is installed.
In other cases, the savings associated with the measure represent a weighted average of
savings for measures reported in the Commonwealth Energy Efficiency Opportunities (EEO)
program and other energy audits.
In confidence, commercial data has also been used to derive installation costs and savings
potentials for some measures, most notably commercial lighting.
Averaging
different items
Energy savings for each measure where the averages of a number of uses of the measure
are reported in EEO and other energy assessments. The aggregation of different instances of
the measure will include the use of different pieces of equipment. The extensive, publicly
available EEO dataset, which was used to derive the average savings for an energy
efficiency measure, was assumed to be representative of the total pool of opportunities in the
wider economy.
Average annual
energy savings
(MJ/yr)
Commercial buildings and SMEs: An average was calculated for annual energy savings for
commercial buildings and SMEs, based on the fraction of the total energy used by the
building or facility resulting from the implementation of the energy efficiency measure.
The baseline and measures developed for the modelling of the National Energy Savings
Initiative [the NESI dataset] also included the average amount of energy used by each type
of building. The product of these two values gives the average annual energy savings.
Industrial facilities: We used the “Percentage of total energy used by a facility that is saved
by the measure” reported in the industrial component of the NESI dataset.3
Measure life
(Years)
This is the estimated length in years that the measure is expected to deliver energy savings
once installed. Sources included the Carbon Trust persistence factor data base, the Low
Carbon Australia persistence factor data base, EES residential baseline study, RIS: NAEEEC
Report 2003/10 Minimum Energy Performance Standards and Alternative Strategies for
Linear Fluorescent Lamps, the BIS Shrapnel Household Appliances 2006 and Energetics
commercial in-confidence figures.
VEET GHG
coefficients
Provided by the Victorian Government and used consistently across all VEET modelling, the
values applied were 0.963 tCO2-e/MWh for electricity and 0.0573 tCO2-e/GJ for natural gas.
Pool of
opportunities
The following approach was used to estimate the number of opportunities for large
commercial and SME buildings:

The total energy consumption for each type of building or SME facility was estimated
using the energy reported by ANZSIC sector, measures of building size and activity as
reported to the ABS (e.g. employee numbers, sales volume, patient numbers, student
numbers) and measures of energy intensity within various types of buildings.
3
Inputs to Energy Savings Initiative modelling from Industrial Energy Efficiency Data Analysis Project:
http://www.industry.gov.au/Energy/Documents/energy-efficiency/energysavings/consultant/Industrial_data_subsector_grouping_level_dataset.xls (Accessed March 2015)
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Item
Details

The average energy used by each type of building or facility was assessed by either:
o
aggregating a set of representative assessments of a specific building type to
directly estimate the average, or
o
estimating the total number of buildings in a specific category and then dividing
the total energy used by those buildings by the total number of buildings.

Using our estimate for the total energy used by each type of building in Victoria, and our
estimate of the average energy used by a building, we estimated the number of buildings
of each type in Victoria.

Using our estimate for the fraction of all buildings or facilities where a measure was
applicable (eg an upgrade to a boiler is only applicable to a building with a boiler) and
our estimate for the fraction of buildings where a particular measure has already been
adopted, we adjusted the estimate of each type of building or facility in Victoria to give
the number of buildings or facilities where a particular measure is still able to be
implemented. This is the pool of opportunities.
The modelling of measures applicable to the large industrial sector used a different approach.
The large industrial sector covered mining and industry excluding non-ferrous metals. The
latter were excluded as non-ferrous metal production is dominated by metal (aluminium)
smelting which takes its electricity directly from the wholesale market. The pool of opportunity
for the industrial measures covers the energy used by the large industrial sector as
determined during the modelling of the national energy savings initiative. This basically
covered the entities that were obligated under the NGER program.
More detail on calculating the pool of opportunity can be found in the report on the
Commercial and SME Energy Efficiency Data on the NESI Consultants Reports webpage.4
Maximum uptake
rate/year
Where a measure is only applicable at the point of replacement of the equipment, the
maximum uptake rate is the total pool of opportunity divided by the life of the equipment ie
the turnover of stock.
In other cases, it was based on our estimate of what is achievable and reasonable. This is
the part of the model where there is the greatest uncertainty
Note that where measures were assessed using a project based method, the maximum takeup in the first year was set to zero to account for the time needed to undertake the
assessment and the internal processes to approve and then implement the measure.
Discount rate
In determining the average number of certificates for a project, the calculated emissions
savings are discounted by 10% for each year of a project’s life up to 10 years. This differs
from the 20% discount rate used in prior VEET modelling.
Average number
of certificates
Where a commercial measure uses a default abatement factor5 to determine the number of
certificates, the number of certificates is equal to the energy savings times the emissions
factors times the measure lifetime.
For measures that are assessed by a project based methodology, the number of certificates
is equal to the energy savings times the emissions factors times 5.5. The latter term
represents 100% of the emissions savings in the first year plus 90% of the emissions savings
in the second year plus 80% of the emissions savings in the third year, and so on.
Additionality
The measures have accounted for regulatory additionally though the definition of the energy
savings due to the measure e.g. the savings due to the installation of an appliance subject to
4
http://www.industry.gov.au/Energy/Documents/energy-efficiency/energysavings/consultant/Commercial_and_SME_EnergyEfficiencyDataReport.pdf (Accessed March 2015)
5
Default abatement factors are used to calculate the number of abatement certificates that may be created from the installation
of common equipment such as compact fluorescent lamps, refrigerated display cabinets and certain electric motors. Calculation
of certificates using default abatement factors is simple as the number of certificates is linked to the size of the appliance and
not the characteristic of the particular installation.
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Item
Details
minimum energy performance standards (MEPS) is taken to be the savings above the MEPS
level not the market average energy performance (assuming the latter is the lower).
Rebound
Rebound in this instance refers to the implementation of a more energy efficient technology
driving a slight increase in the use of the more efficient equipment compared to the previous,
less efficient technology (generally related to the energy cost saving differential). With
deemed abatement this may result in slightly less GHG abatement than anticipated.
The model accounts for rebound by reducing the savings due to an implemented measure
from year to year.6 Our default factor, based on Energetics experience is to reduce the
energy savings by 3% each year and this value was used in the model of the VEET scheme.
Average payback
The average payback is calculated by the model, taking into account the capital cost,
incentive payments and the energy savings.
Payback
installation hurdle
Our default payback thresholds are to include any measure that offers a payback within three
years for measures in large businesses and 1.75 years for the SME sector. Where the takeup is assessed using the payback threshold, 50% of the available instances of the measure
will be taken up when the average payback is equal to the threshold.
Lifetime energy
saved
The lifetime savings for a particular instance of a measure is equal to the sum of annual
savings over the lifetime of the measure.
The total energy saved is the aggregate of energy saved for each instance of each measure,
taking into account the calendar year when the instance was implemented. Discounts to
these savings are applied to measures incentivised using project based assessment
methodologies (see Maximum uptake rate/year).
Annual GHG
emissions saved
This model used an emissions factor equivalent to the VEET GHG coefficient to calculate
annual GHG emissions reduction on a measure by measure basis and in totality.
Lifetime GHG
emissions saved
This is the sum of annual GHG savings across all measures and all years. Lifetime GHG
emissions reductions are also calculated using an emissions factor equivalent to the VEET
GHG coefficient.
Certificate
administrative fee
A further 5% of the certificate price is deducted to account for the cost incurred by the
Accredited Person or third party involved in installing a measure.
Note that costs incurred for the undertaking of a feasibility study prior to implementing the
measure are included in the implementation cost of the measure.
Average cost
The average cost is equal to the cost of applying the measure to the entire building or facility
(equipment + installation + feasibility studies).
The average costs for large commercial and SME measures were derived from the NESI
dataset, unless otherwise indicated in Table 5. Large industrial measures were derived from
the industrial component of the NESI dataset.3
Uptake rate
function
The uptake of a measure is determined by the ratio of the size of the incentive and the cost of
the measure. See Figure 2 for an illustration of an uptake rate function.
6
Note that the year by year reduction in energy savings is independent of the discounting of calculated emissions savings when
determining the number of certificates for project based measures.
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4.
Defining the measures
The energy efficiency measures that were included in the modelling of the extension of the VEET
scheme are based on opportunities in the large industrial, large commercial and SME sectors. They
were developed with reference to Australian and international literature, as well as Energetics’
extensive field experience in conducting energy audits nationwide across most building types.
Each measure was defined by a collection of parameters. Table 3 and Table 4provide details of those
parameters and an example of one activity. Measures were also split between industrial facilities,
commercial buildings and buildings appropriate to the SME sector.
Table 3: Parameters defining each measure
Item
Meaning
Measure name
A descriptive name for the measure.
Building type or sector
Ten types of large commercial buildings, four types of small buildings, industrial
facility. mining facility
Size of opportunity
Number of nominal buildings or nominal facilities where the opportunity exists
Lifetime
Estimate of a particular opportunity useful lifetime
Installed cost
Average cost to implement all instances of the opportunity in the building type or
the facility
Electricity savings
(GJ/p.a.)
Average annual savings from implementing all instances of the opportunity in the
building type or facility
Gas savings (GJ/p.a.)
Average annual savings from implementing all instances of the opportunity in the
building type or facility
T/U function
Used to determine the uptake of a measure, the options were one of three
potential take-up functions or the use of payback in years. There is a default take
up curve plus one for low cost appliances and one for new technologies (where
there can be resistance to early adoption).
T/U rate % size year 1, 2,
3 and 4 and beyond
Maximum limit on uptake: maximum percentage of buildings or facilities that can
be upgraded in any year of the program
P/B Threshold
Three years for large buildings, the industrial sector and the mining sector. 1.75
for the SME sector.
Incentive method
Default abatement factor or project based assessment
Table 4: Example of a measure
Item
Measure Name
ID
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Meaning
Lighting upgrade
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BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
Item
Meaning
Sector
SME industrial
End use
Lighting
Measure type
Size of opportunity (units)
SME-existing
126300
Units
Buildings
Applicable energy tariff
Franchise
Lifetime of abatement savings (years)
10
Total Installed cost ($/unit)
4509.855
Electricity savings (GJ/unit p.a.)
25.67172
Mains Gas savings (GJ/unit p.a.)
0
T/U function
Payback
T/U rate % size year 1
0.15
T/U rate % size year 2
0.15
T/U rate % size year 3
0.15
T/U rate % size year 4 onwards
0.15
Payback Threshold
1.75
Payback SD
Incentive method
4.1.
0.291667
DAF
Large commercial and SME sectors
A number of considerations were taken into account in calculating potential energy savings
attributable to each measure for each building type:
7

The lifetime of a measure: Lifespan estimates were made for each measure with reference
to industry sources7, complemented by Energetics’ industry knowledge.

The minimum energy performance standards (MEPS) applicable to equipment or typical
baseline energy use by equipment in the sample base.

The energy consumed by high efficiency (HE) alternative technologies to existing
installations.
See Table 2.
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
The energy use baseline per building type.
The energy savings potential for each of the measures was expressed as a percentage of the total
energy use by the building type. The marginal or incremental cost per measure relative to the
energy usage of the building type was also calculated based on the capital and implementation cost
estimates from the audit datasets.
The savings potential was assessed for individual measures that were intended as input into the NESI
dataset. We did not take into account the interaction of measures8 nor mutually exclusive measures9.
However, there were only limited instances identified where measures interact with other measures.
The energy efficiency measures included in the model were derived from a similar data set used for
the modelling of the NESI dataset. For commercial and SME applications 38 different measures
across twelve broad classes were modelled. Each measure applied to one or more of ten types of
large commercial building and four types of small to medium enterprises. Types of buildings within the
model include commercial offices, schools, large and small retail outlet, hotels and restaurants.
The list of potential energy savings opportunities in the commercial and SME sectors was supported
with reference to Australian and international literature, as well as Energetics’ extensive field
experience in conducting energy audits nationwide across most building types.
Certain adjustments were made to the list of measures from the earlier work. The key adjustments are
outlined below:

Measures covered by Schedule 1 to Schedule 30 of the VEET Regulations were removed as
they will be covered by the modelling of the residential sector.

Several groups of measures involved the same improvement implemented in different
building types. Further, these measures had the same implementation cost per MJ. These
measured were combined into one measure spanning all buildings covered by the separate
measures with no change in the overall result but with the benefit of less complexity.

With the exception of certain forms of window treatment, building shell measures are not
cost effective. Window treatments are covered by the residential component of the VEET
scheme and so applying treatments on SME premises has been transferred to the residential
model. We validated the remaining window treatment measures that applied to large
commercial buildings. These measures were combined into a single measure applicable to
large commercial buildings. These changes have made no material impact on the results
generated by the model.

Measures involving the installation of evaporative air conditioners were removed as the
commercial sector has seen a steady decline in the installation of evaporative air
conditioners10. This amendment also had no material impact on the results generated by the
model.
8
This refers to a situation where the effectiveness of one measure is impacted by the adoption of a second or third measure.
For example, the replacement of inefficient lighting in an office could lead to increased energy use for heating due to more heat
being lost in the ambient atmosphere by the inefficient lighting.
9
This refers to a situation where the implementation of one measure, precludes the adoption of another.
Institute for Sustainable Systems and Technologies, “ Technical research on evaporative air conditioners and feasibility of
rating their energy performance”, (accessed March 2015)
10
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
Based on experiences with other energy efficiency trading schemes (e.g. the ESS),
upgrades to commercial lighting are expected to be one of the measures that has a large
take-up. Therefore have a robust description for this measure is highly desirable in this
Report. The lighting measures outlined in the 2013 Assumption Report were taken from the
NESI dataset. Better data regarding the savings and costs of commercial lighting upgrades
is now available. This was used to validate and revise the lighting measures. In particular, all
lighting measures were combined into two aggregated measures: one for large commercial
buildings and one for SME buildings. These amendments have resulted in a more accurate
calculation of the likely certificates to be generated under the lighting upgrade measure. A
more comprehensive description of the lighting measures can be found in Appendix A.

There has been almost no take-up of high efficiency (HE) motors in the ESS. The technical
potential for the measure “HE motors in small offices” in the NESI dataset is much higher
than can be justified as small offices do not use pumps other than small pumps in generally
packaged HVAC systems. Based on revised assessment for the HE motor market in the
commercial business sector in Victoria this measure was removed from the current model.
This removal does not impact on the treatment of HE motors in other business sectors such
as warehouses, shopping centres and universities.
The list of measures for energy savings for the large commercial and SME sectors is presented in
Table 5. In several cases the capital costs from the earlier modelling were increased by 15% to
capture the cost of the feasibility study. Previously this was included in the administration fee. This is
described as “the 15% loading” in the table.
Table 5: List of stationary energy savings measures by commercial market segment
DAF/PBA11
Measure Name
Sector
Basis and comments
Air Compressors:
Improved operation
of compressed air
systems
The measure was taken from the NESI SME dataset.
There was some take-up of air compressor measures in
the ESS. The need for a relatively high certificate price
will limit actual take-up.
PBA
SME Industrial
PBA
Appliances &
Equipment: Variable
speed drives (VSDs)
SME Industrial
The measure was taken from the NESI SME dataset.
Several similar VSD measures applicable to the SME
sector were included in the earlier modelling. Further,
some related measures are included in the current
dataset. Therefore as VSDs are largely an industrial
piece of equipment, this measure is restricted to just the
industrial SME sector.
The poor take-up of these apparently cost effective
measures appears to be because take-up was
modelled by an uptake curve rather than payback.
Payback is used in the current modelling.
Appliances &
Equipment: Replace
a MEPS compliant
motor with a HE
motor
These were derived from the NESI dataset. The 15%
loading has been applied.
DAF
Shopping
Centre
11
Note that there has been almost no take-up of high
efficiency motors in the ESS.
DAF means a default abatement factor. PBA means project based assessment.
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Measure Name
Sector
Basis and comments
DAF/PBA11
Appliances &
Equipment: Replace
a MEPS compliant
motor with a HE
motor
DAF
Warehouse
(NR)
HVAC: Replace a
MEPS compliant
motor with a HE
motor
University /
TAFE
Boilers, Furnaces &
Ovens: Upgrade
Hospitality
The measure was taken from the NESI large
commercial dataset.
PBA
Boilers, furnaces and
ovens: Replace boiler
Large
commercial
This combined measure was derived from the NESI
large commercial dataset. The 15% loading has been
applied.
PBA
Building shell:
Window treatment
Large
commercial
The treatment of building shell measures was
discussed above.
PBA
HVAC: HVAC
controls
Hospitality
DAF
PBA
The measures were taken from the NESI datasets.
HVAC: HVAC
controls
PBA
SME Industrial
The measure was derived from the NSEI SME dataset.
The large installation cost of these measures suggests
that they would be better modelled using payback to
determine take-up. A 5% loading was added to the
installation cost to allow for any feasibility studies.
DAF
HVAC: High
efficiency standalone
AC
SME
HVAC: High
efficiency standalone
AC
Large office
HVAC: High
efficiency standalone
AC
Shopping
Centre
Large
commercial
A review of data from sources available to Energetics
suggested that the indicated installation cost per GJ of
electricity saved was too low, and should be at least
$150/GJ. The 15% loading has been applied.
PBA
HVAC: HVAC
controls
HVAC: Replace
cooling tower
Large office
The measure was taken from the NESI large
commercial dataset.
PBA
HVAC: Upgrade
chiller
Large
commercial
This measure was derived from the NESI large
commercial dataset. The 15% loading has been
applied.
PBA
HVAC: Variable
speed drives and
control for fans
Large
commercial
This measure was derived from the NESI large
commercial dataset. The 15% loading has been
applied.
PBA
Lighting upgrade
SME Industrial
Lighting upgrade
Large
commercial
© Energetics Pty Ltd 2016
DAF
The measures were taken from the NESI large
commercial dataset. The test for take-up was changed
to the payback as it better reflects the type of measure
and the large installed cost. A 5% allowance for the
feasibility study has been added.
DAF
DAF
Lighting measures were discussed above.
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Measure Name
Sector
Pumps: Upgrade to
HE pumps
Hospitality
DAF/PBA11
Basis and comments
DAF
The measures were taken from the NESI datasets.
Pumps: Upgrade to
HE pumps
SME Industrial
Pumps: Variable
speed drives for
pumps
Hospital
DAF
PBA
The measures were taken from the NESI datasets.
Pumps: Variable
speed drives for
pumps
4.2.
PBA
SME Industrial
Large industrial sector
In addition to the calculation of potential energy savings from the commercial and SME sectors,
additional work was undertaken to calculate energy savings (electricity and natural gas savings) from
the large industrial sector in Victoria. These sites have been included following the sunsetting of the
Environment and Resource Efficiency Plans (EREP) program. To date large industrial and commercial
sites had been excluded from the coverage of the VEET scheme due to the operation of the EREP
scheme.
In total 26 measures were considered covering both the broad industrial sector and the mining sector.
Note that all measures are based on a PBA assessment of savings.
The bulk of the data used to derive the measures applicable to the large industrial sector has been
extracted from work done by ClimateWorks as part of the modelling of the NESI12. The list of
measures as included in the VEET model is shown in Table 6:
Table 6: List of stationary energy savings measures by industrial market segment
Measure
Industry
Mining
Measures that save electricity
Upgrade: Co-generation or Tri-generation


Upgrade: Comminution (crushing and grinding) and blasting systems
Upgrade: Compressed air systems


Upgrade: Conveyors


Upgrade: Furnace/Kilns

Upgrade: Gas compression equipment

Upgrade: IT, communications and other electronic equipment

Upgrade: Lighting systems


“Inputs to the Energy Savings Initiative modelling from the Industrial Energy Efficiency Data Analysis Project”, ClimateWorks
Australia, July 2012
12
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Measure
Industry
Mining
Upgrade: Non-transport machinery

Upgrade: Other Building services


Upgrade: Other equipment


Upgrade: Pumping systems


Upgrade: Refrigeration

Upgrade: Stationary materials handling systems

Upgrade: Various industrial systems

Upgrade: Ventilation systems, fans and blowers

Upgrade: Waste treatment, disposal and remediation


Measures that save natural gas

Upgrade: Boiler systems


Upgrade: Conveyors
Upgrade: Dryers

Upgrade: Furnace/Kilns



Upgrade: Gas compression equipment
Upgrade: Other process heating equipment

Upgrade: Ovens



Upgrade: Thermal electricity generation

Upgrade: Various industrial systems
The data for individual measures was aggregated by “Technology/ process” and “Fuel category”
across the major industry classifications – “Mining” and “Industry”. Subsector groupings associated
with manufacturing of metals was excluded as they largely reflect energy used by the aluminium
smelters which is not covered by the VEET. The final set of aggregated measures described the
expected savings as a percentage of total electricity or gas used at a facility and the average capital
cost per GJ of energy saved for particular technology or process. The aggregation did not include
measures with paybacks in the 0-2 year range as reported by ClimateWorks as they are likely to be
taken up by businesses without any additional incentives afforded through the VEET.
The model also estimated the energy used by the large industrial sector. Information on energy use in
Australian categorised by fuel type and by ANZSIC sector is available from the Office of the Chief
Economist13. The energy used in Victoria for each ANZSIC sector was estimated by assuming the
13
2014 energy statistics data (http://www.industry.gov.au/industry/Office-of-the-Chief-Economist/Publications/Pages/Australianenergy-statistics.aspx#)
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fraction of energy used by each ANZIC sector in Victoria is the same as the corresponding national
fraction. The electricity and natural gas consumed by Victoria was also available in the 2014 energy
statistics.
Work on the NESI yielded the fraction of each fuel type used by large and SME business. This data
was used to estimate the electricity and gas used by large industry and large mining in Victoria. These
values were within 10% of the reported EREP amounts, which suggests that the majority of facilities
obligated under the EREP program are also the sites that report under NGER. The requirement to
report under NGER was the criteria to separate large businesses from SMEs in the NESI dataset
modelling.
An example of a specific measure by sub-sector and fuel type is outlined below in Table 7.
Table 7: Extract from ClimateWorks database
Item
Typical value
Subsector grouping
C11 - Food Product Manufacturing
Technology/ process
Dryers
Fuel category
Gas
Payback range
>4 years
Energy savings (% subsector
grouping - fuel category energy use)
4.23%
Capital costs ($/GJ)
$41.60
Appendix A provides additional information about the industrial measures including the amount of
energy they save and the cost to implement the measures.
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5.
Outcomes: Results of the modelling
5.1.
Business sector results
Figure 5 to Figure 7 below show the results of the modelling of the business sector of the VEET
scheme. It considers three or five year timeframes of the VEET scheme, and forecasts the take-up of
certificates at varying certificate prices. Note that neither Figure 5 nor Figure 6 include the possible
generation of certificates from large business (as outlined in section 4.2).
Figure 5: Three year target with large business exclusion
Figure 6: Five year target with large business exclusion
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Figure 7 below includes large business in the modelling of total certificates created leading to the
higher level of certificates created, particularly in years 2018 and 2019. The approach taken to include
large industrial sector energy users is outlined further in section 4.2.
Figure 7: Five year target without large business exclusion
As demonstrated in both Figure 6 and Figure 7 some drop off is assumed at a higher certificate price.
This results from a higher certificate price driving increased participation in the earlier years, and
limiting the pool of opportunity for participation in the later years. This is particularly so where large
business’ are excluded. As Figure 6 demonstrates there is a levelling off after a certain certificate
price.
5.2.
Results for certificate price scenarios
The generation of certificates for each specific measure was based on two different scenarios – a
three year scenario and a five year scenario – with yearly certificate prices modelled against three
different VEET targets. Table 8 and Table 9 below consider the certificate prices that were used to
model the results in each scenario against each certificate target.
Table 8: Three year scenario certificate prices
Certificate Target
2016
2017
2018
5,400,000
19.53
30.73
27.04
5,800,000
23.30
37.04
28.56
6,200,000
30.77
44.15
30.26
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Table 9: Five year scenario certificate prices
Certificate Target
2016
2017
2018
2019
2020
5,400,000
19.53
30.73
27.04
25.86
51.30
5,800,000
23.30
37.04
28.56
28.41
54.47
6,200,000
30.77
44.15
30.26
30.75
57.65
Based on these certificates the following total certificate prices were generated. These totals
incorporate all measures and assumptions outlined within this Report.
Table 10 provides an overview of the total certificates created at each certificate target over the three
year VEET scenario.
Table 10: Certificates generated in the three year VEET scenario
Certificate Target
2016
2017
2018
5,400,000
1,139,016
2,257,823
2,937,394
5,800,000
1,169,056
2,400,504
3,335,132
6,200,000
1,195,707
2,582,105
3,402,405
Table 11 provides an overview of the total certificates created at each certificate target over the five
year VEET scenario. Note that the remainder of the certificates generated in each of the scenarios
outlined in Table 10 and Table 11 arise from the residential sector.
Table 11: Certificates generated in five year VEET scenario
Certificate Target
2016
2017
2018
2019
2020
5,400,000
1,139,016
2,257,823
2,937,394
3,136,295
4,074,539
5,800,000
1,169,056
2,400,504
3,335,132
3,581,499
3,533,575
6,200,000
1,195,707
2,582,105
3,402,405
3,699,273
3,767,856
Table 12 gives a complete breakdown of certificated generated for each measure over the five year
period for an indicative target of 5.4 million certificates.
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Table 12: Certificates generated by measure in 5.4 million certificates, five year VEET scenario14
Measure Name
Sector
End use
2016
2017
2018
2019
2020
Air Compressors: Improved operation of
compressed air systems
SME Industrial
Air Compressors
0
0
0
0
0
Appliances & Equipment: Variable speed drives
SME Industrial
Appliances and equipment
2,930
8,723
6,791
9,197
179,859
Appliances & Equipment: Replace a MEPS
compliant motor with a HE motor
Shopping Centre
Appliances and equipment
3,793
3,793
3,793
3,793
3,793
Appliances & Equipment: Replace a MEPS
compliant motor with a HE motor
Warehouse (NR)
Appliances and equipment
2,630
2,630
2,630
2,630
2,630
Boilers, Furnaces & Ovens: Upgrade
Hospitality
Boilers, furnaces and ovens
0
319
246
359
11,482
Boilers, furnaces and ovens: Replace boiler
Large commercial
Boilers, furnaces and ovens
52,354
56,867
51,282
13,263
0
Building shell: Window treatment
Large commercial
Building shell upgrade
1
1
2
4
331
HVAC: HVAC controls
Hospitality
HVAC
0
0
0
0
0
HVAC: HVAC controls
SME Industrial
HVAC
0
0
0
0
0
HVAC: High efficiency stand alone AC
SME
HVAC
0
0
0
0
0
HVAC: High efficiency stand alone AC
Large office
HVAC
0
0
0
0
0
HVAC: High efficiency stand alone AC
Shopping Centre
HVAC
0
0
0
0
0
HVAC: HVAC controls
Large commercial
HVAC
0
27,334
35,821
17,783
0
14
In the context of this Report “small offices” and “small trade” captures tenancies in large commercial buildings and large shopping centres
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Measure Name
Sector
End use
2016
2017
2018
2019
2020
HVAC: Replace a MEPS compliant motor with a
HE motor
University / TAFE
HVAC
2,926
2,926
2,926
2,926
2,926
HVAC: Replace cooling tower
Large office
HVAC
0
0
0
0
0
HVAC: Upgrade chiller
Large commercial
HVAC
0
0
0
0
0
HVAC: Variable speed drives and control for fans
Large commercial
HVAC
37,466
124,038
120,934
28,948
0
Lighting upgrade
SME
Lighting
748,040
1,513,131
1,918,612
1,958,276
1,392,327
Lighting upgrade
Large commercial
Lighting
0
0
0
0
0
Pumps: Upgrade to HE pumps
Hospitality
Pumps
0
9,761
9,337
7,351
9,761
Pumps: Upgrade to HE pumps
SME Industrial
Pumps
133,575
133,575
133,575
133,575
133,575
Pumps: Variable speed drives for pumps
Hospital
Pumps
0
0
0
0
0
Pumps: Variable speed drives for pumps
SME Industrial
Pumps
77,181
158,295
132,213
141,710
158,953
Refrigeration: RDC upgrade
Hospitality
Refrigeration
21,120
21,120
21,120
21,120
21,120
Refrigeration: RDC upgrade
Small trade
Refrigeration
32,871
32,871
32,871
32,871
32,871
Refrigeration: HE commercial refrigeration
Large retail (R)
Refrigeration
5,576
8,254
7,193
4,855
2,126
Refrigeration: HE commercial refrigeration
SME Industrial
Refrigeration
6,574
11,324
10,333
14,745
51,917
Refrigeration: Replace a low efficiency fan motor
with an electronically commutated motor
Large retail (R)
Refrigeration
11,979
24,062
40,173
3,818
0
Ventilation / fans: Car park ventilation control
Large office
Ventilation and fans
0
0
0
0
0
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Measure Name
Sector
End use
2016
2017
2018
2019
2020
Ventilation / Fans: Improve fan efficiency
SME
Ventilation and fans
0
0
0
0
0
Water heating: Solar or heat pump water heater
Hospital
Water heating
0
2
1
3
1,711
Water heating: Solar or heat pump water heater
Large retail (R)
Water heating
0
1
0
1
595
Upgrade: Co-generation or Tri-generation
Industry
Co-generation or Tri-generation
0
0
0
0
0
Upgrade: Compressed air systems
Industry
Compressed air systems
0
0
0
0
0
Upgrade: Conveyors
Industry
Conveyors
0
0
7
20
16
Upgrade: Furnace/Kilns
Industry
Furnace/Kilns
0
0
6
53
0
Upgrade: Gas compression equipment
Industry
Gas compression equipment
0
0
0
6,147
0
Upgrade: IT, communications and other
electronic equipment
Industry
IT, communications and other
electronic equipment
0
0
0
0
3
Upgrade: Lighting systems
Industry
Lighting systems
0
0
0
0
0
Upgrade: Non-transport machinery
Industry
Non-transport machinery
0
7
7
13
268
Upgrade: Other Building services
Industry
Other Building services
0
9,922
55,158
138,227
68,859
Upgrade: Other equipment
Industry
Other equipment
0
9
57
64
147
Upgrade: Pumping systems
Industry
Pumping systems
0
4,766
19,257
21,719
61,626
Upgrade: Refrigeration
Industry
Refrigeration
0
7
7
18
1,313
Upgrade: Stationary materials handling systems
Industry
Stationary materials handling
systems
0
0
0
0
0
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Measure Name
Sector
End use
2016
2017
2018
2019
2020
Upgrade: Various industrial systems
Industry
Various industrial systems
0
40,998
38,147
60,835
855,519
Upgrade: Ventilation systems, fans and blowers
Industry
Ventilation systems, fans and
blowers
0
523
6,409
10,152
14,660
Upgrade: Waste treatment, disposal and
remediation
Industry
Waste treatment, disposal and
remediation
0
8
8
11
107
Upgrade: Comminution (crushing and grinding)
and blasting systems
Mining
Comminution (crushing and
grinding) and blasting systems
0
0
0
4,026
0
Upgrade: Compressed air systems
Mining
Compressed air systems
0
0
0
4,015
0
Upgrade: Conveyors
Mining
Conveyors
0
5
5
12
265
Upgrade: Lighting systems
Mining
Lighting systems
0
9
35
45
85
Upgrade: Other Building services
Mining
Other Building services
0
7,108
29,528
35,558
73,519
Upgrade: Other equipment
Mining
Other equipment
0
0
0
0
0
Upgrade: Pumping systems
Mining
Pumping systems
0
0
0
0
0
Upgrade: Stationary materials handling systems
Mining
Stationary materials handling
systems
0
0
0
0
0
Upgrade: Boiler systems
Industry
Boiler systems
0
0
155,370
395,601
838,602
Upgrade: Dryers
Industry
Dryers
0
19,353
58,171
39,633
94,291
Upgrade: Furnace/Kilns
Industry
Furnace/Kilns
0
0
0
0
0
Upgrade: Other process heating equipment
Industry
Other process heating
equipment
0
0
0
0
0
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Measure Name
Sector
End use
2016
2017
2018
2019
2020
Upgrade: Ovens
Industry
Ovens
0
0
0
0
0
Upgrade: Various industrial systems
Industry
Various industrial systems
0
36,060
45,336
22,905
59,248
Upgrade: Boiler systems
Mining
Boiler systems
0
0
0
0
0
Upgrade: Conveyors
Mining
Conveyors
0
0
0
0
0
Upgrade: Furnace/Kilns
Mining
Furnace/Kilns
0
22
32
13
34
Upgrade: Gas compression equipment
Mining
Gas compression equipment
0
0
0
0
0
Upgrade: Other process heating equipment
Mining
Other process heating
equipment
0
0
0
0
0
Upgrade: Thermal electricity generation
Mining
Thermal electricity generation
0
0
0
0
0
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Appendix A.
Key assumptions
Retail energy prices
These feed directly into the payback calculation that determines the take-up of measures, and a small
change in the retail price can have a significant impact on the cost effectiveness of measures e.g. a
10% change in the electricity price to SMEs is roughly equivalent to a change in certificate price of
$20/tonne. The electricity prices must be marginal prices, representing the cost of the electricity that is
actually saved due to the measures.
The retail prices out to 2024 in the model are in Table 13.
Table 13: Model retail energy prices
Sector and fuel
2016
2017
2018
2019
2020
2021
2022
2023
2024
Franchise (SME) customers
Electricity ($/MWh)
207.22
200.63
203.88
209.36
214.39
210.79
214.28
217.49
221.29
Natural gas ($/GJ)
11.17
11.98
12.42
11.95
11.07
10.27
9.55
9.59
9.62
Contract (large) customers
Electricity ($/MWh)
158.52
151.90
154.85
159.95
164.63
160.91
164.08
166.98
170.45
Natural gas ($/GJ)
10.77
11.58
12.02
11.55
10.67
9.87
9.15
9.19
9.22
Savings and cost of lighting upgrades
These are expected to be the measures with the highest uptake in the SME and commercial sectors,
and so accurate modelling of these measures will increase confidence in the outcomes of the
modelling. Key data items are the cost of implementation per unit of energy saved, savings per
instance of a measure and the number of measures that can be implemented.
Implementation costs
Energetics analysed the actual implementation cost and savings achieved for a large number of
commercial lighting upgrades for confidential and non-confidential sources. We found that
implementation costs ranged from $32/GJ saved up to $278/GJ saved. Averages, weighted by the
number and size of projects were $175/GJ for the SME sector and $135/GJ for the large commercial
sector. These results reflected a typical basket of lighting measures that are actually being
implemented in the respective sectors.
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For comparison, the simple average of lighting measures in the earlier VEET modelling was $156/GJ.
The NSW OEH recently published a technology report on energy efficient lighting 15. This report
included typical savings and costs for commercial lighting upgrades. The cost of various low cost
upgrades ranged for $64/GJ (replacing a 60W dichroic halogen lamp with a 25W IRC lamp) through to
$237/GJ (replacing a twin 36 W T8 recessed linear fluorescent luminaire with a single 36 W T8
reflector). The simple average of these lighting upgrades was around $150/GJ.
These comparisons suggest that using values of $175/GJ for the SME sector and $135/GJ for the
large commercial sector is not unreasonable.
Savings per instance of a measure
The savings per instance of a measure is required to determine the number of instances that can be
implemented. The average savings per installation across a range of actual lighting upgrades in our
databases is in Table 14.
Table 14: Savings per lighting installation
Sector
Large commercial
SME
Average use per
site (MWh)
Savings as % of site
consumption
Savings/instance
(MWh)
5000
2.71%
136
86
8.33%
7.1
The OEH technology report on energy efficient lighting quotes the annual energy savings for the
upgrading of 100 lights of different types, with the annual savings ranging from 5.2 MWh to 80 MWh.
Lighting upgrades typical of SMEs saved the order of 10 MWh per 100 lights. The figure of 7.1 MWh
per instance in the table implies that a typical SME lighting upgrade involves around 70 to 100 lights.
This seems reasonable.
The figure of 5000 MWh for large commercial sites was derived from values reported in the NESI
dataset. The following chart was taken from the NESI Consultants Report Webpage16 (refer Figure 8).
15
http://www.environment.nsw.gov.au/resources/business/140017-energy-efficient-lighting-tech-rpt.pdf (Accessed March 2015)
16
http://www.industry.gov.au/Energy/Documents/energy-efficiency/energysavings/consultant/Commercial_and_SME_EnergyEfficiencyDataReport.pdf (Accessed March 2015).
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16,000
14,000
13,676
12,000
10,000
8,479
8,000
5,439
6,000
5,265
5,179
3,440
4,000
3,161
2,729
1,908
2,000
1,045
0
School
Large retail
(NR)
Shopping centre
Warehouse
(NR)
Large retail (R)
Warehouse (R)
Large office
CBD Hotel / SA
Hospital
University /
Tertiary
Annual electricity consumption (MWh)
BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
Figure 8: Large commercial site energy consumption
Potential instances of lighting upgrades
The potential number of instances of lighting upgrades comes from a consideration of the energy used
by the SME and large commercial sectors. Estimates of the energy used by these sectors come from
the NESI dataset modelling, refer Table 15.
Table 15: Energy consumption by building class
Energetics Building Class
Electricity consumption by
building class in Victoria (PJ)
Sector
CBD Hotel / SA
0.76
Large Com
School
0.98
Large Com
University / Tertiary
2.70
Large Com
Hospital
1.39
Large Com
Large retail (R)
3.57
Large Com
Large Retail (NR)
1.25
Large Com
Warehouse (R)
0.49
Large Com
Warehouse (NR)
2.13
Large Com
Large office
3.96
Large Com
Shopping Centre
2.75
Large Com
Street lighting
1.24
Large Com
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Energetics Building Class
Electricity consumption by
building class in Victoria (PJ)
Sector
Non-CBD hotel/hostel/resort
2.05
SME
Restaurant
5.53
SME
Small retailing facilities
8.13
SME
Small office
17.81
SME
SME Manufacturing
22.12
SME
0
SME
SME Industrial (other / NMF)
Knowing the energy used by the sectors in Victoria and the average energy used per site means that
the number of potential sites can be estimated. Many of the sites will already have undertaken lighting
upgrades and so must be removed from the set of potential sites. Based on analysis done during the
NESI dataset modelling, we estimated that 40% of large buildings and 30% of small buildings already
had upgraded lights.
The derivation of the potential for commercial lighting upgrades in Victoria is in Table 16.
Table 16: Derivation for commercial lighting upgrades in Victoria
Sector
Total electricity
use in Victoria
(GWh)
Average
use per site
(MWh)
Estimated
penetration to
date
Technical
potential
(Instances)
Potential
certificates
Large commercial
5,893
5000
40%
710
966,000
SME
15,455
86
30%
126300
9,016,000
The final column in the figure is the number of certificates that would be generated if all possible
measures were implemented. It assumes a 10 year lifetime for the measures. The uptake of
commercial lighting in the ESS generated around 1 million certificates in the first year, rising to 3
million in the third year. Assuming that the market in Victoria is similar to that in NSW, we constrained
the uptake in the first three years of the modelled scheme to 10%, 20% and 30% of the maximum.
Payback thresholds
A review of the prevailing thresholds applied to energy efficiency investment by Australian businesses
was carried out as part of the NESI dataset modelling. This review suggested that SMEs generally
require paybacks of between one to 2.5 years, whilst large commercial entities may respond positively
to paybacks of between one to four years, depending on economic conditions in each case. The
payback threshold for large commercial entities is three years during average economic conditions.
During times of weak economic growth the payback threshold approaches one year and in good times
it increases to four years. There was a large variation in the average payback period of opportunities
between measures and end-use categories.
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BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
We used 1.75 years for the payback threshold for the SME sector. A figure of 3 years was used for the
large commercial and industrial sectors.
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Appendix B.
Industrial and mining measures
Table 17: Industrial and mining measure parameters
Measure
Total energy used by
all facilities in Victoria
where the measure
applies (TJ)
Percentage of total
energy used by a
facility that is saved
by the measure
Cost to
implement the
measure ($/GJ
saved)
Measures applicable to industry that save electricity
Co-generation or Tri-generation
12,986
18.3%
$50.87
Comminution (crushing and grinding)
and blasting systems
12,986
0.4%
$8.95
Compressed air systems
38,957
0.1%
$45.50
Conveyors
12,986
0.0%
$1.50
Furnace/Kilns
12,986
0.0%
$1.60
Gas compression equipment
38,957
0.1%
$35.40
IT, communications and other
electronic equipment
12,986
0.0%
$31.67
Lighting systems
12,986
0.1%
$12.91
Non-transport machinery
25,971
0.0%
$33.96
Other Building services
38,957
0.3%
$65.77
Other equipment
12,986
0.0%
$1.70
Pumping systems
38,957
0.3%
$66.71
Refrigeration
38,957
1.0%
$102.12
Stationary materials handling systems
12,986
0.0%
$28.62
Various industrial systems
103,885
7.0%
$246.66
Ventilation systems, fans and blowers
38,957
0.1%
$62.44
Waste treatment, disposal and
remediation
12,986
0.0%
$28.22
Measures applicable to mining that save electricity
Comminution (crushing and grinding)
and blasting systems
11,171
0.2%
$63.38
Compressed air systems
11,171
0.2%
$63.77
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BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
Measure
Total energy used by
all facilities in Victoria
where the measure
applies (TJ)
Percentage of total
energy used by a
facility that is saved
by the measure
Cost to
implement the
measure ($/GJ
saved)
Conveyors
16,756
0.3%
$186.96
Lighting systems
5,585
0.0%
$5.71
Other Building services
22,341
0.3%
$105.73
Other equipment
16,756
1.0%
$89.47
Pumping systems
11,171
0.0%
$87.42
Stationary materials handling systems
5,585
0.0%
$39.09
Measures applicable to industry that save natural gas
Boiler systems
217,643
3.1%
$24.65
Dryers
108,821
1.8%
$17.81
Furnace/Kilns
54,411
0.0%
$0.10
Other process heating equipment
108,821
0.5%
$19.05
Ovens
54,411
0.1%
$7.03
Various industrial systems
272,054
2.9%
$48.38
Measures applicable to mining that save natural gas
Boiler systems
10,734
0.1%
$3.85
Conveyors
10,734
0.0%
$38.79
Furnace/Kilns
10,734
0.3%
$1.63
Gas compression equipment
10,734
0.9%
$128.26
Other process heating equipment
10,734
0.3%
$8.93
Thermal electricity generation
10,734
0.1%
$3.72
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Appendix C.
Details of the measures
An extract from the VEET model that includes the descriptions of all the measures in the model is
attached. See “Measures.xlsx”.
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BUSINESS SECTOR ENERGY EFFICIENCY MODELLING
Contact details
Brisbane
Perth
Level 12, 410 Queen St, Brisbane Qld 4000
Level 3, 182 St Georges Tce, Perth WA 6000
Ph: +61 7 3230 8800
Ph: +61 8 9429 6400
Fax: +61 2 9929 3922
Fax: +61 2 9929 3922
Canberra
Sydney
Unit 2, 6 Napier Cl, Deakin ACT 2600
Level 7, 132 Arthur St, North Sydney NSW 2060
Ph: +61 2 6101 2300
PO Box 294 North Sydney NSW 2059
Fax: +61 2 9929 3922
Ph: +61 2 9929 3911
Fax: +61 2 9929 3922
Melbourne
web
www.energetics.com.au
Level 6, 34 Queen St, Melbourne VIC 3000
abn
67 001 204 039
PO Box 652, CSW Melbourne VIC 8007
acn
001 204 039
Ph: +61 3 9691 5500
afsl
329935
Fax: +61 2 9929 3922
Energetics is a carbon neutral company
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